3.2.4 - Computer Output

3.2.4 - Computer Output

10th - 12th Grade

14 Qs

quiz-placeholder

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3.2.4 - Computer Output

3.2.4 - Computer Output

Assessment

Quiz

Mathematics

10th - 12th Grade

Hard

CCSS
HSS.ID.C.7, HSS.ID.C.8, HSS.ID.B.6

+4

Standards-aligned

Created by

Shelli Temple

Used 11+ times

FREE Resource

14 questions

Show all answers

1.

MULTIPLE CHOICE QUESTION

2 mins • 1 pt

Media Image

The computer output below shows the result of a linear regression analysis for predicting the concentration of zinc, in parts per million (ppm), from the concentration of lead, in ppm, found in fish from a certain river. Which of the following statements is a correct interpretation of the value 19.0 in the output?

On average there is a predicted increase of 19.0 ppm in concentration of lead for every increase of 1 ppm in concentration of zinc found in the fish.

On average there is a predicted increase of 19.0 ppm in concentration of zinc for every increase of 1 ppm in concentration of lead found in the fish.

The predicted concentration of zinc is 19.0 ppm in fish with no concentration of lead.

The predicted concentration of lead is 19.0 ppm in fish with no concentration of zinc.

Approximately 19% of the variability in the zinc concentration is predicted by its linear relationship with lead concentration.

Tags

CCSS.HSS.ID.C.7

2.

MULTIPLE CHOICE QUESTION

2 mins • 1 pt

Media Image

Given the following Minitab output, which of the following is false?

80% of the variability in y is explained by the linear relationship with x.

Since r=0.898, the linear relationship between x and y is strong, positive, and linear.

As x increases by one unit, y decreases, on average, by 1.6914 units.

The intercept of the least squares regression line is -0.868.

The equation of the least squares regression line is y=-0.868-1.6914x.

Tags

CCSS.HSS.ID.C.7

CCSS.HSS.ID.C.8

3.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Media Image

Above is the scatter plot (with the least squares regression line) for calories and protein (in grams) in one cup of 11 varieties of dried beans. The computer output for this regression is included. Which of the following best describes what the number s=3.37648 represents?

The slope of the regression line is 3.37648.

The standard deviation of the explanatory variable, calories, is 3.37648.

The average error when using the LSRL to make predictions.

The ratio of the standard deviation of protein to the standard deviation of calories is 3.37648.

Tags

CCSS.HSS.ID.B.6

CCSS.HSS.ID.C.7

4.

MULTIPLE CHOICE QUESTION

45 sec • 1 pt

Media Image
The computer output is used to predict helicopter flight time from drop height.  Which is the correct equation for this relationship?
(Time) = -0.03761+0.0057244(drop height)
(time) = -0.03761+0.05838(drop height)
(height)=-0.03761+0.0057244(time)
(height)=0.0057244-0.03761(time)

Tags

CCSS.HSA.CED.A.2

CCSS.HSA.SSE.A.1

CCSS.HSF.BF.A.1

CCSS.HSF.LE.A.2

CCSS.HSS.ID.C.7

5.

MULTIPLE CHOICE QUESTION

45 sec • 1 pt

Media Image
Given the image of linear regression computer output, what would the correlation coefficient be?
.922
.96
-0.03761
28.37

Tags

CCSS.HSS.ID.C.8

6.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Media Image
The following computer output describes the relationship between y = height (in cm) and x = foot length (also in cm) for 12 randomly selected students from the British Census @ Schools database. The scatterplot for this relationship show a roughly linear shape. Which of the following is an equation of least-squares regression line for these data?
Height = 117.99 + 1.878 (Foot Length)
Foot Length = 117.99 + 1.878 (Height)
Height = 1.878 + 117.99 (Foot Length)
Foot Length = 1.878 + 117.99 (Height)

Tags

CCSS.HSA.CED.A.2

CCSS.HSS.ID.B.6

CCSS.HSS.ID.C.7

CCSS.HSS.ID.C.8

7.

MULTIPLE CHOICE QUESTION

2 mins • 1 pt

Data obtained from a group of high school seniors comparing age and the number of hours spent on the telephone. The resulting regression equation is

Predicted number of hours = 0.123(age)+2.57 with r =0.866

What percentage of the variation in the number of hours spent on the telephone can be explained by this least-squares regression model?

0.75%

75%

0.866%

86.6%

This value cannot be found with the given information.

Tags

CCSS.HSS.ID.C.8

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